Title :
A survey of intelligent network fault diagnosis technology
Author :
Lv Feng ; Li Xiang ; Wang Xiu-qing
Author_Institution :
Coll. of Phys. Sci. & Inf. Eng., Hebei Normal Univ., Shijiazhuang, China
Abstract :
This paper firstly discusses the common fault types of networks, and the necessity and importance of intelligent fault diagnosis for networks. Secondly, the basic process for network diagnosis systems is put forward. Thirdly, the basic idea and various popular methods of network fault diagnosis based on the intelligent technology, such as: Expert System, Bayesian Network, Rough Set and Neural Networks, are reviewed. Finally, the existing problems and the future research direction for network fault diagnosis are discussed.
Keywords :
artificial intelligence; computer network reliability; fault diagnosis; fault tolerant computing; Bayesian network; expert system; intelligent network fault diagnosis technology; network diagnosis systems; neural networks; rough set; Computers; Data models; Educational institutions; Fault diagnosis; Neural networks; Support vector machines; Training; Data Mining; Machine Learning; Network Fault Diagnosis; Pattern Recognition;
Conference_Titel :
Control and Decision Conference (CCDC), 2013 25th Chinese
Conference_Location :
Guiyang
Print_ISBN :
978-1-4673-5533-9
DOI :
10.1109/CCDC.2013.6561817
